Information System Tools Research Articles

Electronic medical information systems and timeliness of care in the emergency department: a scoping review

BackgroundAlthough many emergency department (ED) settings have implemented an electronic medical information system (EMIS) and EMIS tools in an effort to improve timeliness of care outcomes, there remains a paucity of scientific information on this topic. We therefore performed a scoping review to describe the range of EMIS interventions and their impacts on time-based outcomes in the ED.MethodsWe searched four bibliographic databases to identify potentially relevant records published after 2014 in English. Two reviewers assessed records for eligibility using a two-step screening process. We then extracted data on the type of EMIS, outcomes assessed, and reported results. Findings were summarized in tabular form and grouped by time-based outcome.ResultsTwenty-five studies met the eligibility criteria, with approximately half being retrospective studies. Interventions varied among studies; they generally included a new or updated EMIS, EMIS tools related to disease diagnosis and/or management, triage tools, or health information exchange platforms. Included studies compared interventions with relevant comparator groups, such as prior versions of an EMIS, absence of an EMIS, pen-and-paper documentation, and/or communication via telephone and fax. The most common outcomes reported were length of stay (n = 17 studies) and time to medication (n = 6 studies), followed by time to order, time to provider, and time from result to disposition. Reported effects of the interventions were generally inconsistent, showing either improvements, delays, or no change in examined outcomes.ConclusionsAdditional research is needed to determine how electronic medical information may be used in the ED to improve timeliness of care. Findings from this review can be used to inform future systematic reviews that evaluate the impact of these systems and tools on specific quality of care measures.

Assessment of Soil Erosion within the Gayathripuzha River Basin Using RUSLE Model and GIS Tools

Soil erosion, a natural phenomenon accelerated by human activities, became a major problem for agricultural land use and for water quality concerns. Soil erosion by water is influenced by various factors like climate, nature of land surface, slope steepness, soil properties, land cover, and management practices. Estimation of soil erosion is essential to know the nature and quantity of soil loss and create specific strategies for soil conservation. This research paper thoroughly examines the susceptibility of soil erosion in the Gayathripuzha river basin in Kerala, India, which is encompassing a wide area of around 961 km². Employing the Revised Universal Soil Loss Equation (RUSLE), this investigation assesses the influential factors affecting soil erosion, which comprise rainfall (R Factor), soil erodibility (K Factor), topography (LS Factor), land usage (C Factor), and the impact of conservation measures (P Factor). The study was conducted using Geographic Information System (GIS) tools like ArcGIS 10.8 Desktop and integrating data on rainfall, soil properties, land topographic features, and land use. Rainfall erosivity is a major factor causing erosion in Gayathripuzha river basin and it ranges from 746.03 to 1222.35 MJ mm ha−1 h−1 y−1 in the river basin. Soil erodibility factor also varies widely within the region. Slope length and steepness factor showed that highland ecosystems are present only in a small area of the river basin. Variation in land use and land cover also influenced the soil erosion within the area. The estimated average annual soil erosion ranges from 0 to 133.18 t ha-1 yr-1 within the research site. The research found that soil erosion varied greatly across the study area. Regions with slopes over 50% had much higher erosion rates, while most of the study area had low erosion levels. Notably, the intensity of soil erosion demonstrated a positive correlation with slope percentage, with areas classified as bare ground demonstrating the highest erosion rates. These findings emphasize the necessity for targeted and comprehensive conservation strategies tailored to the diverse landscape of the region to effectively manage soil erosion and mitigate its adverse impacts.

ANALYSIS OF SUITABLE DUMP SITES IN KAFANCHAN, JEMA’A LOCAL GOVERNMENT AREA KADUNA STATE, NIGERIA

The research focuses on assessing the suitability of dump sites for solid waste disposal in Kafanchan town, Kaduna state, utilizing Surveying and Geo informatics techniques. With the escalating environmental impact of waste due to population growth, urbanization, and industrialization, the study aims to identify appropriate locations for waste disposal. The methodology employs Geographic Information System (GIS) tools, involving the overlaying of datasets and criteria such as drainage, land use, and road networks. The process includes investigating solid waste disposal in Kafanchan, acquiring data through a Global Positioning System (GPS) receiver, converting criteria into GIS layers, and processing the collected information on a computer system using ArcGIS software. The spatial analysis reveals potential sites suitable for solid waste disposal based on connectivity, contiguity, and overlay methods. The results advocate for the effectiveness of GIS in promptly selecting suitable waste disposal sites. The conclusion emphasizes the recommendation to adopt the identified sites for solid waste disposal in the area. Overall, the study underscores the significance of GIS in addressing contemporary environmental challenges related to waste management and highlights the practical application of spatial tools for sustainable solutions.

Storm's influence on long-term shoreline evolution along Casablanca-Mohammedia (Morocco)

Coastal erosion assessment has emerged as one of the most significant instruments for making decisions and offering effective solutions for coastal regions. Mohammedia-Casablanca's shoreline constantly changes due to natural and man-made erosion and accretion. This research uses historical aerial photographs, wave analysis data, geographic information system (GIS) tools, and statistical methods to evaluate spatial and temporal shoreline changes from 1969 to 2020. The analysis of storminess and rates of shoreline change is also discussed jointly in three sediment cells. For this, energy parameters are determined to characterize storm-induced impacts. The Digital Shoreline Analysis System (DSAS) calculated shoreline change using End Point Rate (EPR), Shoreline Change Envelope (SCE), and Net Shoreline Movement (NSM) methods. Out of 2477 transects placed at 30-meter intervals along the study area, approximately 39% of the transects show erosion, and the rest indicate accretion (61%). Over the entire study period (51 years), the analysis of shoreline evolution does not show a clear correlation with storm parameters. The only period in which the shoreline shift correlates with storm activity is 1969–1982. Storms were frequent and intense during this time, and the erosion was at its maximum (over 66% of the coastline). Outside this period, accretion has occurred even during periods of intense storms, as was the case here between 2009 and 2020, when accretion affected 70.1% of the Mohammadia-Casablanca coastline. This suggests that the recent installation of marine structures (groynes, seawalls, dikes, jetties, and piers) multiplied after 1982 has positively affected the rate of coastal erosion.

Detection of karst depression in Brazil comparing different semantic and instance segmentations and global digital elevation models

This research assessed the efficacy of deep segmentation in identifying and measuring natural karst depressions in the Bambuí Group's carbonate rocks in Western Bahia, Brazil. The investigation used five Global Digital Elevation Models (DEMs) with 30-m resolution: Advanced Spaceborne Thermal Emission and Reflection Radiometer - Global Digital Elevation Model version 3 (ASTER-GDEM v3), Advanced Land Observing Satellite World 3D – 30 m version 3.2 (AW3D30 v3.2), Copernicus 30 m global DEM (GLO-30), NASA Digital Elevation Model version 1 (NASADEM v1), and Shuttle Radar Topography Mission version 3 (SRTM v3). The karst feature detection analysis compared five semantic segmentation architectures: Feature Pyramid Networks (FPN), LinkNet, UNet, UNet++, DVL3+, using an EfficientNet-B7 backbone, one instance segmentation model (Mask-RCNN), and a semantic-to-instance conversion method. This comparison considers different datasets, including one, two, or eleven variables (DEM, DEM-based sink depth, and nine terrain attributes). Besides, we performed a combinatorial analysis of the DEMs to evaluate the improvement in karst feature detection. The methodology involved the generation of geomorphometric attributes, sample labeling from Sentinel-2 and Operational Land Imager-Landsat 8 datasets, training-validation-testing steps with 128 × 128 samples, reconstruction of large images for semantic and instance segmentation, and accuracy analysis. The findings revealed that GLO-30 and AW3D30 data were the most accurate, while ASTER GDEM performed poorly in both segmentation forms. Among the semantic models, FPN showed the highest accuracy. The 11-variable models preferentially outperformed those with fewer in both types of segmentation. The approach of semantic-to-instance conversion with Geographic Information System tools favored individualizing karst depressions and obtaining efficient quantification, consisting of an easy alternative to achieve instance segmentation. Reconstruction of large remote sensing images through sliding windows considering the specifics of instance and semantic segmentation demonstrated that smaller stride enhances object coverage and reduces the risk of losing crucial information, effectively improving the predictions. The combinatorial analysis for semantic and instance segmentation indicates that models incorporating more DEMs (4- and 5-DEM models) and variables achieve generally higher accuracy. The best result in semantic segmentation was combining the five DEM datasets using 11 variables, reaching an F-score of 85.06 and IoU of 74.00. In instance segmentation, the best result for the bounding box was the model that integrates AW3D30, GLO-30, NASADEM, and SRTM with eleven variables reaching Average Precision (AP) of 45.64, AP50 of 88.40 and AP75 of 39.38, while the best result for the segmentation mask was the model that integrates the five models with eleven variables with AP of 42.61, AP50 of 86.79 and AP75 of 35.43. These results demonstrate that integrating a wide range of DEM data, even the lowest performing ones, improves model generalization and accuracy in segmentation, leveraging strengths and mitigating individual weaknesses. Future work could explore high-resolution DEMs and the integration of various deep-learning methods.

Socio-environmental and technical factors assessment of photovoltaic hydrogen production in Antofagasta, Chile

This study introduces a method for identifying territories ideal for establishing photovoltaic (PV) plants for green hydrogen (GH2) production in the Antofagasta region of northern Chile, a location celebrated for its outstanding solar energy potential. Assessing the viability of PV plant installation necessitates a balanced consideration of technical aspects and socio-environmental constraints, such as the proximity to areas of ecological importance and indigenous communities, to identify potential zones for solar and non-conventional renewable energy (NCRE)-based hydrogen production.To tackle this challenge, we propose a methodology that utilizes geospatial analysis, integrating Geographic Information System (GIS) tools with sensitivity analysis, to determine the most suitable sites for PV plant installation in the Antofagasta region. Our geospatial analysis employs the QGIS software to identify these optimal locations, while sensitivity analysis uses the Sørensen–Dice coefficient method to assess the similarity among chosen socio-environmental variables.Applying this methodology to the Antofagasta region reveals that a significant area within a 15 km radius of existing road networks and electrical substations is favorable for photovoltaic projects. Our sensitivity analysis further highlights the limiting effects of socio-environmental factors and their interactions. Moreover, our research finds that enlarging areas of socio-environmental importance could increase the total hydrogen production by about 10% per commune, indicating the impact of these factors on the potential for renewable energy production.

Determination of the Groundwater Potential Zones in Babylon Using Remote Sensing & GIS Techniques

Freshwater found underground in the tiny spaces (pores) of soil and rocks is known as groundwater. Groundwater is a valuable resource that considerably contributes to the yearly supplies. To preserve water quality and oversee groundwater systems, evaluation of the potential zone of groundwater recharge is crucial. Using remote sensing and Geographic Information System (GIS) tools, groundwater potential zones are identified. This study proposes to use satellite imagery and the software program (ArcGIS) to find a groundwater potential zone in Babylon City, Iraq. A groundwater map has been created using various data, namely slope, drainage density, lineament density, land use/land cover, geology type, soil type, and rainfall map. All these data are collected using a weighted overlay tool. Five categories were created based on the groundwater results: very poor, poor, moderate, good, and exceptional. The 'good' class covers about 32% of the study area. The current study shows that excellent groundwater class exists in Al-Hindiyah Dam, Al-Muhaweel, Al-Midhatiyah, Al-Kifil, and Al-Mashrua’a. The excellent groundwater class in Al-Shommali covers approximately 198.0054 km2. Certain areas like Al-Musaib Center, Al-Hilla Center, Al-Hashimiyah, and Abi Garaq don't have much groundwater. The moderate and excellent classes cover around 19% of the study area. The main conclusion is that Remote Sensing and GIS have gained recognition as a practical approach to mapping groundwater potential zones due to their ability to integrate diverse spatial data.

NETWORK ANALYSIS FOR THE STUDY OF TRANSPORT IN THE METROPOLITAN AREA OF ALGEIRS

Transport in the metropolitan area of Algiers is very complicated, so we used the powerful tools of geographic information systems in the analysis of transport in the study area. Through the utilization of network analysis and GIS capabilities, our study focuses on optimizing transportation networks and enhancing port accessibility in the metropolitan regions of Boumerdes, Blida, Tipaza, and Algiers. Our methodology involves data collection, GIS analysis, and mapping to generate databases and maps of metropolitan networks. Through assessing port accessibility, road connectivity, and population-based hotspots analysis. Our study reveals Algiers as the most accessible municipality, attributed to its strong centralization. The roadbased analysis and population-based hotspot analysis provide valuable insights into port accessibility, road connectivity, and high-density townships, facilitating informed urban planning and infrastructure development.

Ghost Gears in the Gulf of Gabès: Alarming Situation and Sustainable Solution Perspectives

This study represents a first step in investigating the prevalence, causes, and spatial distribution of Abandoned, Lost, or Discarded Fishing Gears (ALDFGs) in the Gulf of Gabès, a critical fishing area in Tunisia. Five main fishing gear types—benthic trawls, encircling nets, longlines, gillnets, and trammel nets were analysed for their loss rates and contributing factors. The study involved extensive surveys among local fishermen and the use of geographic information system (GIS) tools for spatial mapping. The findings reveal varying loss rates among different gear types, with longlines experiencing the highest losses (59%), followed by trammel nets (45%), gillnets (40%), trawls (38%), and encircling nets (36%). Causes of gear loss include entanglement on obstructions, conflicts with other fishing gears, entanglement with marine animals, adverse weather conditions, and intentional dumping at sea. The study highlights the challenges posed by the consistent increase in fishing effort in the region. Spatial distribution mapping indicates two significant concentrations of ALDFGs, correlating with specific fishing activities and depths. The study emphasizes the importance of addressing gear losses as a threat to marine biodiversity and ecosystem health. Recommendations for mitigation include improving boat equipment, raising awareness among fishermen, implementing effective waste management, and exploring economic incentives for ALDFG recovery. This research contributes essential insights for fisheries management, environmental conservation, and sustainable practices in the Gulf of Gabès. Collaborative efforts are crucial for developing and implementing strategies that minimize the impact of ALDFGs on the marine environment while supporting the socio-economic interests of fishermen.

Implementing policies to mitigate urban heat islands: Analyzing urban development factors with an innovative machine learning approach

Taiwan is located in a hot and humid subtropical climate. Urban development, building heat emissions, and human activities lead to the urban heat island (UHI) effect in which urban air temperatures are significantly higher than those in the surrounding suburban areas. In this study, the factors contributing to the UHI effect were investigated in a case study of Taichung City, Taiwan by using high-resolution geographic climate data. Geographic Information System tools were used for grid-based spatial data analysis, and a physiological equivalent temperature index map was calculated and overlaid to identify heat zones. The results revealed that environmental factors have complex, nonlinear effects on temperatures in in urban areas; hence, the analysis was challenging. The decision tree algorithm was used to identified key environmental factors contributing to urban heat in areas with different levels of development; a weighting analysis was then performed to select effective urban cooling strategies. Finally, backpropagation neural network models tailored to different development levels were used for simulations to validate the proposed cooling policies. The results of this study were incorporated into the urban planning policies of Taichung City, Taiwan to mitigate the UHI effect and create a more suitable urban living environment.

Use of GIS and RS Tools for Analysis of Land Use Land Cover and Land Surface Temperature: A Case Study of District Khairpur, Pakistan

Land use and land cover (LULC) monitoring plays an important role in sustainable planning and management of resources. This research focuses on analysing historical LULC changes over the Khairpur district of Sindh province of Pakistan. Remote Sensing and Geographic Information System (RS & GIS) tools have been employed using the maximum likelihood algorithm of the supervised classification method. Temporal data of the latest high-resolution satellite imagery provided by NASA GLCF (Global Land Cover Facility), Landsat 8 Operational Land Imager (OLI), and Landsat 4, 5 Thematic Mapper (TM) for 2001, 2010, 2015, and 2020 were acquired from Earth Explorer of United States Geological Survey (USGS). The study area is classified into four major classes namely Barren Land, Vegetation, Built-up areas, and Water Bodies. Analysis revealed that for 2001 and 2005 there was no change in barren land area, whereas in 2010 slight decrease in barren land was found which further decreased for the analysis period of 2020, overall barren land class decreased at a rate of 07% (i.e., 74% to 67%) during the analysis period. Also, vegetation and water bodies classes experienced variations throughout the analysis period, however built-up areas showed constant increase throughout the analysis period where built-up area classes increased from 9% to 15%. Whereas land surface temperature (LST) throughout the analysis period showed increasing trends, for both high ranges and low ranges. It was analysed that the areas having dominancy of the barren land class experienced the highest temperature ranges whereas low temperature ranges were discernible in the areas having vegetation covers. It can be concluded from the study that barren land covers the major area of the study area and there is an increase in built-up areas which can further enhance the LST in the study area.

The Effect of Revitalisation on the Value of Residential Premises in Historic Urban Layouts

Abstract The aim of this research was to analyze the effects of revitalization activities performed in a selected historical urban layout using the mixed method in which statistical analysis was supported by Geographic Information System (GIS) tools on the price level of residential premises on the secondary market. The subject of the analyses is “Old” Nowa Huta (Krakow, Poland), which was designed as an ideal independent city in the mid-20th century. The analysis covered the period from January 1, 2007 to December 31, 2020. The conducted analyses have demonstrated that the transaction prices (and hence the value) of residential premises located in “Old” Nowa Huta increased during the performed revitalization activities. However, based on the results obtained, it could not be confirmed that this was the direct result of the revitalization itself, because the price level within the research site increased in proportion to the rising prices in the entire city. It seems, however, that although the changes in the quality of space in the analyzed area are not spectacular, they serve to improve the quality of life of the local community and are one of the ways to protect this historic urban layout.

Reflection on Five Months Rural District Hospital Posting of Final Year MBBS Students

Patan Academy of Health Sciences has been sending its undergraduate medical students to ruralpostings aligning with the national health system of Nepal to produce competent and empathetichealthcare professionals as a part of its social accountability. One such rural posting is a 20-weeklongdistrict posting where students are posted at district hospital and district health office. Wewere final-year students posted at Gulmi district for this purpose in the year 2021/22. We learnedthe functioning of a district hospital along with different clinical skills. We also learned to use thedistrict health information system and different qualitative tools in drafting district health reportsand strategic planning under the guidance of the District Health Office. Such exposure of medicalstudents is essential to develop competent and empathetic health professionals and similar provisionsshould be included in the undergraduate curriculum of other universities.

Examining Technology Use and Competence of Higher Education Academics During the COVID-19 Pandemic

Objectives: The present study describes the utilization frequency and competencies of educational technologies among academics at a university in Turkey during the COVID-19 pandemic. Methods: Participants were 391 faculty members and lecturers working in the faculties and vocational schools of a Turkish university during the 2020–2021 academic year. A survey included questions regarding the use of educational technologies and perceived competency in the use of those technologies. Results: Academics are more familiar with distance education than hybrid or blended learning. Academics reported that blended learning, hybrid learning, and distance education provide more effective education on integrating technology but report that they mostly prefer face-to-face teaching after the COVID-19 pandemic. The top three self-reported competencies are MS Office, the university academic information system, and meeting and course management tools. More information is needed about educational technology approaches and various applications such as augmented reality, simulations, assessments, and video tools. Conclusion: Faculty use of digital tools is limited, they experience significant deficiencies in using various digital tools and systems, and they are less competent in applying these tools. Academics still consider traditional face-to-face teaching as the primary choice if they are free to make decisions in the context of education and training. Thus, there is a need for professional development focused on pedagogical educational technology approaches, models, and methodologies. Implications: Various factors such as the course type, subject matter, education level, technical infrastructure, and technological and methodological support should be evaluated within the context of digitizing universities.

Sustainable affordances of information systems for cultural tourism: An organisational aesthetics perspective

AbstractAlthough information systems (IS) are increasingly used to provide sustainable solutions for tourism, our understanding of the social mechanisms whereby IS contribute to a sustainable visitor economy is limited. This paper fills the gap by investigating how organisations enact the affordances of IS in preserving intangible cultural heritage (ICH) to contribute to a sustainable visitor economy. Using an organisational aesthetics perspective, we explore the mechanisms through an in‐depth case study of an ICH‐based company in Jingdezhen, a famous historical porcelain city in China. Through the effective use of IS tools, the case organisation has successfully transformed from a ceramic manufacturing plant to a popular tourist attraction. Our study unveils six sustainable affordances of IS in three dimensions, wherein ICH aesthetics act as direct stimuli, knowledge tools and experiences. Affordances emerge from the processes of both creating and managing aesthetics. By enacting these affordances, the case organisation builds a more profound engagement with online audiences, attracts more ICH visitors and transfers ICH knowledge to potential inheritors of the tradition, creating a sustainable visitor economy. Our findings, summarised into a sustainable affordances model, contribute to the IS for sustainable tourism literature by shedding light on the black box of the social mechanisms of IS‐enabled ICH preservation. The sustainable affordances model can also help ICH‐based organisations reflect on how to build a sustainable visitor economy using IS.

Assessing carbon storage and sequestration benefits of urban greening in Nador City, Morocco, utilizing GIS and the InVEST model

In the 21st century, tackling climate change is an important challenge, and the absorption of CO2 via urban greening employing photosynthesis offers a potential answer to the climate issue. Within this work, the city of Nador is chosen as a case study. The initiative in question proposes an enhanced technique focused on estimating the advantages of urban greening in terms of carbon storage and sequestration. This technique combines the use of Geographic Information Systems (GIS) tools and the InVEST model, enabling the study of land use and land cover (LULC) scenarios within the location. These scenarios contain numerous alternatives, ranging from the adoption of intense and extensive green roofs to the establishment of gardens and woodland areas. The carbon storage modeling technique depends on the exploitation of land use maps, reinforced by a bibliographic examination of the key carbon reservoirs. The analysis of results from biophysical modeling indicates a considerable increase of over 45.36 % compared to the existing condition when the option of extensive green roofs is chosen. In the setting of extensive green roofs, this rise reaches a rate of 64.20 %. Furthermore, the restoration of the Gourougou forest north of the city leads to an increase of 70.30 %. The adoption of diverse combinations, such as the integration of green roofs with urban vegetation, greatly helps to further enhancing carbon storage. From a financial perspective, the additional value can range from $2,012,825.16 to $3,601,025.53, depending on the chosen scenario. This financial assessment highlights the possible advantages that might be converted into carbon credits in return for emission reduction, partially offsetting the expenses associated with the adoption of each greening solution. Ultimately, these findings give a chance for urban planners and green architecture professionals to perform in-depth planning analyses.

The Multi–Disaster risk assessment: A-GIS based approach for Izmir City

Urban settlements currently face many disasters that are increasing in number and frequency every day such as floods, landslides, sea level rise, storms, drought, forest fires, etc. due to the negative consequences of global climate change caused by significantly exceeding the carrying capacity of nature. Cities are currently becoming less resistant to disaster risks because of the unhealthy settlements. These settlements are becoming widespread in terms of physical, economic and social conditions as a natural result of the urbanization in which planning processes are carried out in an uncontrolled and unsupervised manner. This situation makes it a necessity to develop strategies and policies aimed at reducing and/or eliminating possible disaster damages which are defined as high risk. From this viewpoint, the study aims to reveal the current disaster risks in urban areas with a dense population and building stock. Izmir city is determined as the study area. Spatial analyses are performed for disaster risk by using Geographical Information Systems (GIS) tools and Weighted Overlap method considering the natural and built environment elements that significantly affect the disaster risk. The findings obtained from the study and the determinations made within the scope of the Izmir Provincial Disaster Risk Reduction Plan (IRAP) prepared by the Disaster and Emergency Management Presidency (AFAD) are evaluated comparatively. As a result, it has been seen that the determinations put forward for disaster risks have shown consistency throughout Izmir city and the studies carried out at the local level have been prioritized in such a way as to be aimed at risk management and prevention planning by the time.

Spatio-temporal investigation of urbanization and its impact on habitat fragmentation in natural ecosystems of Istanbul using Shannon’s entropy and landscape metrics in GIS

This study aims to investigate the impact of spatio-temporal dynamics of urban sprawl on habitats in Istanbul, using the CORINE 1990 and 2018 land cover datasets. In this context, by means of geographic information system (GIS) tools and techniques, land cover maps are created for land cover change analysis and visualization, the Shannon’s entropy method is performed for measuring urban growth and sprawl, and the landscape metrics method is applied for assessing habitat loss and fragmentation. Results indicate that the rate of urban sprawl in the area increased by 0.1230 as per the Shannon’s entropy index over the 28-year period. Similarly, the Shannon Diversity Index and the Shannon Evenness Index rose from 1.74 to 1.85 and from 0.68 to 0.70, respectively, indicating an increase in urbanization within the area. Moreover, an analysis of patch numbers reveals that habitat fragmentation increased in shrub and/or herbaceous vegetation associations (72.55%), heterogeneous agricultural areas (45.11%), arable lands (42.5%), forests (36.13%) and pastures (15.05%), due to urbanization. Habitat fragmentation has had a detrimental effect on the local biodiversity. While 15 flora species were identified as vulnerable, 13 as endangered and 9 as critically endangered, 19 fauna species were identified as vulnerable and 5 as endangered. This study highlights that the natural habitats and biodiversity of Istanbul will suffer further decline due to urbanization unless sustainable urban planning and management policies are put into practice. It is essential to have controlled urban development to preserve the ecosystem’s carrying capacity, and urbanization decisions must consider this requirement.

Mapping of soil suitability for medicinal plants using machine learning methods

Inadequate conservation of medicinal plants can affect their productivity. Traditional assessments and strategies are often time-consuming and linked with errors. Utilizing herbs has been an integral part of the traditional system of medicine for centuries. However, its sustainability and conservation are critical due to climate change, over-harvesting and habitat loss. The study reveals how machine learning algorithms, geographic information systems (GIS) being a powerful tool for mapping and spatial analysis, and soil information can contribute to a swift decision-making approach for actual forethought and intensify the productivity of vulnerable curative plants of specific regions to promote drug discovery. The data analysis based on machine learning and data mining techniques over the soil, medicinal plants and GIS information can predict quick and effective results on a map to nurture the growth of the herbs. The work incorporates the construction of a novel dataset by using the quantum geographic information system tool and recommends the vulnerable herbs by implementing different supervised algorithms such as extra tree classifier (EXTC), random forest, bagging classifier, extreme gradient boosting and k nearest neighbor. Two unique approaches suggested for the user by using EXTC, firstly, for a given subregion type, its suitable soil classes and secondly, for soil type from the user, its respective subregion labels are revealed, finally, potential medicinal herbs and their conservation status are visualised using the choropleth map for classified soil/subregion. The research concludes on EXTC as it showcases outstanding performance for both soil and subregion classifications compared to other models, with an accuracy rate of 99.01% and 98.76%, respectively. The approach focuses on serving as a comprehensive and swift reference for the general public, bioscience researchers, and conservationists interested in conserving medicinal herbs based on soil availability or specific regions through maps.

Characterization of spatio-temporal dynamics of the constrained network of the filamentous fungus Podospora anserina using a geomatics-based approach.

In their natural environment, fungi are subjected to a wide variety of environmental stresses which they must cope with by constantly adapting the architecture of their growing network. In this work, our objective was to finely characterize the thallus development of the filamentous fungus Podospora anserina subjected to different constraints that are simple to implement in vitro and that can be considered as relevant environmental stresses, such as a nutrient-poor environment or non-optimal temperatures. At the Petri dish scale, the observations showed that the fungal thallus is differentially affected (thallus diameter, mycelium aspect) according to the stresses but these observations remain qualitative. At the hyphal scale, we showed that the extraction of the usual quantities (i.e. apex, node, length) does not allow to distinguish the different thallus under stress, these quantities being globally affected by the application of a stress in comparison with a thallus having grown under optimal conditions. Thanks to an original geomatics-based approach based on the use of automatized Geographic Information System (GIS) tools, we were able to produce maps and metrics characterizing the growth dynamics of the networks and then to highlight some very different dynamics of network densification according to the applied stresses. The fungal thallus is then considered as a map and we are no longer interested in the quantity of material (hyphae) produced but in the empty spaces between the hyphae, the intra-thallus surfaces. This study contributes to a better understanding of how filamentous fungi adapt the growth and densification of their network to potentially adverse environmental changes.